This disclosure relates generally to correcting non-uniformity defects in a printed image, and more particularly to a method of correcting for spatial variation within scanning bars.
In the past, scanners have been made either as moving spot scanners, in which a single sensor and light source sequentially scan in across a page in a fast scan direction, and then advance to a next position in a slow scan direction before scanning again in the fast scan direction; or as full width array scanners, in which a large collection of sensors and one or more light sources simultaneously capture information from an entire line of the page in the Full width array type scanners have more complex electronic devices but simpler electro-mechanical systems. For a given speed, they also have much lower bandwidth requirements at the sensor, and lower light level requirements, such that the sensor obtains enough photons in the time it spends at a given position. For these reasons and others, full width array scanners have become the low cost option in recent years.
As is generally the case when multiple sensors are used to measure a single phenomenon, the outputs of the various sensors are not identical when the input values are. This is partially due to sensor noise, (which is not systematic), and partially due to manufacturing variability in the sensors themselves. FIG. 1 shows a schematic of one full width array color scan bar, with the view of the bar from the paper being scanned. Color filters of three colors, a row of red filters 120, green filters 130, and blue filters 140, as well as a row of clear filters 110, are deposited at regular intervals on the surface of the bar. The “slow-scan direction” indicated in FIG. 1 is the direction of paper feed in the marking system, and the “fast-scan direction” is the direction substantially perpendicular to the slow-scan direction. FIG. 2 shows the same bar, in side view. Light flowing through the filters 210 strikes the CCD sensors which comprise (among other components) a gating layer, an epitaxial layer 220, and a substrate 230. Charges travel through the epitaxial layer, primarily downward, with the amount of charge proportional to the amount of light passing through each filter. The amount of charge passing through the epitaxial layer is converted to a digital value and reported as the amount of a given color at a given location.
One source of variability in the amount of light sensed is variation in the thickness of the color filter. Others include manufacturing variations in the thickness and physical makeup of the epitaxial layer. As a result there are variations in the amount of light required at any given location along the array to produce the same digital value. In order to reduce this variability a bar may be calibrated by illuminating a strip of a constant white reflectance with a uniform illumination, and exposing the scan bar to the light reflected from this strip. A difficulty with this method is that the quality of the calibration is only as good as the uniformity of the white strip. Strips with reflectance variation of approximately 1% or less are readily available: strips with reflectance variation of 0.1% or less are very difficult and expensive to manufacture. For most consumer applications a 1% reflectance variation is more than sufficient for the task. For some sensing applications, where the scanner is being used as a measuring device, rather than an image sensor, tighter tolerances are required. For example, in the application exemplified by U.S. Pat. No. 6,760,056 to Klassen et al., an objective is to correct variations sensed on a page, and caused by a printing device. It is well-known (see, e.g., Basic Statistics by Kemele, Schmidt and Berdine, ISBN 1-880156-06-7, p 9-76) that in order to measure an effect and correct it, the measuring system needs to have a tenth the variation of the effect being corrected. Thus, if variation of 1% reflectance is the tolerable limit for a printer's output, the sensor must have variation of less than 0.1%.
However, even if the variability of the calibration strip were zero, there would still be the possibility for the introduction of variability, as illustrated by FIG. 3. Because of the geometry of the sensors, some charge from the red light migrates from the clear to the red sensor; some migrates to the green sensor; some charge from green migrates from clear and green to red, and from green to blue; and some charge from blue migrates from blue to green and from clear to red. Because sensor-to-sensor variability is calibrated out under white light, these charge migrations are compensated for when white or grey is scanned. However, in the case of a red region of a page, no charges generated by the green or blue components of the light migrate to adjacent sensors, since there are negligible green or blue components of the light. Any variation in the green filter has no effect on the charges received at the red sensor, but because the calibration was done with white light, variation in the green filter is included in the correction for non-uniformity. Therefore the non-uniformity is over-corrected for red, resulting in an appearance of non-uniformity, even after calibration with a perfectly uniform calibration strip. When the corrected grey is uniform to within 0.3%, “corrected” red has been observed to exhibit up to 5% variation. Various methods exist of improving the uniformity of the scan bar and calibration strip, however they may be too expensive for common use.
All U.S. patents and published U.S. patent applications cited herein are fully incorporated by reference. The following patents or publications are noted:
U.S. Pat. No. 6,554,388 to Wong et al. (“Method for Improving Printer Uniformity”) describes generating a test print having a series of test patches or zones with predetermined density levels. A scanner scans the test print to obtain density value readings within each test density zone for each pixel that corresponds to each exposure element. Density value readings are averaged and the difference in measurement from this average is used to compute a correction factor for each individual exposure element. An image data manager conditions the input data by the correction factor, then sends the conditioned image data to the image forming assembly for printing.
U.S. Pat. No. 6,571,000 to Rasmussen et al. (“Image Processing Algorithm for Characterization of Uniformity of Printed Images”) teaches an image quality metric directed to printed images which are intended to have a uniform color, but which show visible color variations. The color variation may take various forms, both with respect to the type of color difference and with respect to the spatial nature of the non-uniformities. The image quality analysis system distinguishes between non-uniformities in the categories of amplitude modulated cluster dot halftone patterns, frequency modulated halftone patterns, irregular two-dimensional variations from noise, isolated (non-periodic) one-dimensional streaks, periodic, one-dimensional bands, and two-dimensional periodic variations. The results from the image quality analysis are then used as a basis for diagnosing machine problems.
U.S. Pat. No. 6,760,056 to Klassen et al. (“Macro Uniformity Correction for X-Y Separable Non-Uniformity”) describes a method of rendering a raster output level and determining an image position of a pixel of interest within an image. An intended raster output level, which corresponds to the pixel of interest, is received into a processing device. A final raster input level is determined as a function of the image position and the intended raster output level. The final input level and the image position are transmitted to an output device. An actual raster output level is rendered, via the output device, at a position on an output medium corresponding to the image position. The actual raster output level substantially matches the intended raster output level.
U.S. Pat. No. 6,943,919 to Barnick (“Method and Apparatus for Correcting Defects in a Spatial Light Modulator Based Printing System”) teaches transmitting a digital image to at least one spatial light modulator and capturing the resulting image. The variation in intensity between each image pixel and at least one reference image pixel is compared and a correction factor is derived. The correction gain at each code value for each image pixel is determined and the correction factor is applied with the gain to the digital image.
U.S. Patent Application Publication No. 2004/0136013 to Mestha et al. (“Systems and Methods for Obtaining a Spatial Color Profile, and Calibrating a Marking System”) describes obtaining tone reproduction curves for calibrating a marking system using a test pattern with a plurality of patches extending in two directions and crossing each other. Reflectance values are obtained from the first and second test patches. A set of gray balanced tone reproduction curves are obtained based on the reflectance values of the first test patches, and a set of spatial gray balanced tone reproduction curves are obtained based on the reflectance values of the second test patches.
U.S. Patent Application Publication No. 2005/0071104 to Viturro et al. (“Method for Calibrating a Marking System to Maintain Color Output Consistency Across Multiple Printers”) teaches a method for maintaining consistent color output across printers even when the inline sensors have differences in accuracy due to various technical and environmental factors. A spectrophotometer is used to measure the color quality of printed references. Adjustments are then iteratively made until reference charts of desired color quality are obtained. Using the printed reference measured by the inline sensor, control systems of each machine are calibrated. At customer sites and at suitable intervals, a referent document can be read using the inline sensor on a reference machine and any differences from expected values can be calibrated out.
The disclosed embodiments provide examples of improved solutions to the problems noted in the above Background discussion and the art cited therein. There is shown in these examples an improved method for identifying and correcting for spatial variation within scanning bars. The method includes performing diagnostic scans of at least one sheet, in which at least one sheet is scanned in various orientations and translations, with each of the orientations identified. The diagnostic scans are registered with one of the individual diagnostic scans to produce registered scans. The registered scans are averaged to create a master scan corresponding to the sheet, such that the master scan is indicative of the spatial variation within the at least one sheet.
In another embodiment there is disclosed a system for identifying and correcting for spatial variation within scanning bars. The system includes means for performing diagnostic scans of at least one sheet, in which at least one sheet is scanned in various orientations and translations, with each of the orientations identified. The diagnostic scans are registered with one of the individual diagnostic scans to produce registered scans. The registered scans are then averaged to create a master scan corresponding to the sheet, such that the master scan is indicative of the spatial variation within the at least one sheet.